Cytoscape is an open source bioinformatics platform for visualizing molecular interaction networks and integrating these with expression profiles and other high throughput data sets. This wiki contains supporting documentation for Cytoscape Automation scripters and developers.
Resources are organized into categories below, leveraging R and Python libraries:
For tutorial examples, check out the collection of tutorial presentations and protocols.
Additional recommended resources for getting started include Understanding Automation and the FAQ.
|Automation in Java App Development
||Using Automation to Test your app
||How to add Automation to web page
Notebooks and Scripts
R Notebooks and scripts
Select from the examples described below or go straight to the collection of Cytoscape Rmd Notebooks
|rWikiPathways and RCy3
|How to work with pathways in Cytoscape by combining the usage of the rWikiPathways package for WikiPathways and the RCy3 pacakge
Workshops and Use Cases
|Cytoscape Automation with RCy3
|Introduction to using Bioconductor package RCy3 to directly communicate with Cytoscape from R. Three use cases are demonstrated including querying existing interaction databases with a set of genes to create network, creating a correlation network using aMatReader, and a basic enrichment analysis. Workshop given at BIOC2018.
|Cancer Networks and Data
|An R Markdown Vignette that encapsulates a bioinformatics analysis of TCGA data on breast and ovarian cancer in the context of STRING networks
|Pathway Analysis with WikiPathways
|Covers a wide range of analytical and visualization techniques involved in a typical pathway analysis. You will be performing functional enrichment analysis on a differential gene expression dataset that compares lung cancer biopses versus normal tissue. The enrichment analysis will be performed against Gene Ontology, as an introduction to the most common type of enrichment, commonly referred to as GO Analysis. This will serve as the foundation for more advanced enrichment analysis against a pathway database, which is called Pathway Analysis.
|Advanced View API
|Sample Jupyter Notebook to demonstrate how users can manipulate Cytoscape network views directly from Python code
|Copycat layout via CyRest
|Python notebook with instructions and sample code for calling copycat layout through Cytoscape CyREST endpoints
|Cytoscape Reactome FI Example
|This example demonstrates a workflow using ReactomeFIViz CyREST API to perform a comparison pathway and network analysis for TCGA BRCA (breast invasive carcinoma) and OV (ovarian serous cystadenocarcinoma) mutation data
For App Developers
How to add Automation to an App you already maintain
How to build CI Responses for your Automation Functions.
How to access an app's automation features from clients, web browsers, and the Swagger UI
A collection of sample Apps that implement Cytoscape Automation
How to write integration tests in a scripting language to test your App
... to follow when implementing Cytoscape Functions via JAX-RS
... to follow when documenting automation functions
... to follow when implementing Cytoscape Commands
How to add Automation to web page
Join the Community
Please feel free to use, share, copy or adapt any of the materials you find here. They are all implicitly published under the CC0 waiver for maximum reuse potential.
Contact Cytoscape Help Desk with any questions about Cytoscape usage.
To report any issues with the tutorial content, click "Issues" above and open a new issue.